In the spring of 2011, my George Mason University colleague Tyler Cowen published a widely read treatise titled The Great Stagnation arguing that the good ideas, that is to say, the best ideas, for moving human societies forward have already been discovered and put into practice. While the economic crisis, fiscal irresponsibility, and other transient factors may have contributed to the “Great Recession” in the United States, Cowen argues that the roots of America’s economic slowdown are deeper: we have picked the “low-hanging fruit” of technological progress, and as a consequence, further economic advance will be slower and less dramatic than it was the past. If prosperity feeds at the banquet table of knowledge, then we’re down to the leftovers. In Cowen’s words,

The American economy has enjoyed lots of low-hanging fruit since at least the seventeenth century, whether it be free land, lots of immigrant labor, or powerful new technologies. Yet during the last forty years, that low-hanging fruit started disappearing, and we started pretending it was still there. We have failed to recognize that we are at a technological plateau and the trees are more bare than we would like to think. That’s it. That is what has gone wrong.

Cowen substantiates his claim with a carefully constructed fact-based argument, but his strongest points are still the intuitive ones. Think of a person born in the United States in 1891 or thereabouts (my paternal grandmother, for example) who looked out at the world on her sixtieth birthday, in 1951. The reality before her would have been almost wholly unimaginable at the time of her birth. Electric lights, the telephone, automobiles and airplanes, even flush toilets. All of these would have been either extremely rare or nonexistent in her childhood. But what of someone born in 1951 looking at the world today? Sure, we have cell phones and Facebook. The tools of medicine are quite a bit fancier. But, fundamentally, the architecture of modern life has not changed much. A US household today is only incrementally different from a US household sixty years ago. That, essentially, is the core point of The Great Stagnation.

Cowen goes on to note that most of the technologies that have defined the modern world—those that would have seemed marvelous to my grandmother on her sixtieth birthday—were first introduced at the end of the nineteenth century. Their impact on the economy peaked in the 1920s and 1930s. It was these technologies that drove the growth in both industry and government during the Industrial Age—the age of economies of scale that I described in chapter 1. The story of the social and economic changes wrought by these new technologies is, as I have argued, the economic subtext of the twentieth century. Cowen is not alone in making this argument. Venture capitalist and entrepreneur Peter Thiel similarly received considerable attention for a fall 2011 piece in TheNational Review titled “The End of the Future.” New York Times economics correspondent David Leonhardt echoed the themes in The Great Stagnation in an essay titled “The Depression: If Only Things Were That Good” that pointed to a surprising contrast between short-term and long-term trends at the time of the Great Depression:

Underneath the misery of the Great Depression, the United States economy was quietly making enormous strides during the 1930s. Television and nylon stockings were invented. Refrigerators and washing machines turned into mass-market products. Railroads became faster and roads smoother and wider. As the economic historian Alexander J. Field has said, the 1930s constituted “the most technologically progressive decade of the century.” Economists often distinguish between cyclical trends and secular trends—which is to say, between short-term fluctuations and longterm changes in the basic structure of the economy. No decade points to the difference quite like the 1930s: cyclically, the worst decade of the 20th century, and yet, secularly, one of the best.

All is well so far. But, haven’t similar predictions of impending technological stagnation been made—and proved wrong—before? Yes, on a fairly regular basis. In fact, the last flurry of techno-pessimistic outpouring was in the in the 1920s and 1930s—exactly the time when, as Cowen and Leonhardt both accurately report, the great inventions responsible for past prosperity were peaking in terms of their aggregate impact. In chapter 1, I quoted John Maynard Keynes, who stated in 1929 that “it is common to hear people say that the epoch of enormous economic progress which characterized the nineteenth century is over; that the rapid improvement in the standard of living is now going to slow down.” Similarly, here is Joseph Schumpeter himself, in a chapter from Capitalism, Socialism, and Democracy titled “The Vanishing of Investment Opportunity,” paraphrasing the view of his own techno-pessimistic contemporaries:

Most of my fellow economists [ feel that] we have been witnessing not merely a depression and a bad recovery, accentuated perhaps by anti-capitalist policies, but the symptoms of a permanent loss of vitality which must be expected to go on and to supply the dominating theme for the remaining movements of the capitalist symphony; hence no inference as to the future can be drawn from the functioning of the capitalist engine and of its performance in the past.

This is about as succinct a summary as is possible of the arguments recently advanced by Cowen, Thiel, and Leonhardt.

Of course, the mere fact that arguments similar to those in The Great Stagnation have been advanced, and proven incorrect, in the past does not prove that contemporary versions are without merit. As I expect is evident both from my summary of Cowen’s argument and my decision to feature it here, I am largely in agreement with at least one dimension of the core point he is making: that both scientific invention and market-based innovation are, in some sense, getting more difficult as time goes by.

Some years ago I organized a panel at a meeting held at the Kauffman Foundation in Kansas City (where I am currently affiliated) that focused on the relationship between technological complexity and the long-term future of innovation. Among the panelists who consented to participate was Ben Jones, a brilliant young economist recently graduated from the doctoral program at MIT. At the meeting, Jones summarized findings from two of his papers, “The Burden of Knowledge and the ‘Death of the Renaissance Man’: Is Innovation Getting Harder?” and “Age and Great Invention.” These papers intrigued me because they offered a painstakingly argued validation of a conjecture I had been forming in my own mind at the time—that increases in the complexity of technology compelled scientists to specialize ever more narrowly in order to make significant advances, but at the same time they increased the returns to the difficult task of bridging disciplines to create fundamentally new economic combinations.

Jones found that the average age at which great inventors arrived at their breakthroughs was about six years later for inventors working at the end of the twentieth century than for those working at the beginning of the twentieth century. This finding supports the notion that the “lowhanging fruit” of scientific discovery has been harvested by earlier generations; as a consequence, for any given scientist, future advance will be increasingly challenging. Young scientists can compensate for this increasing “knowledge burden,” as Jones terms it, by specializing ever more narrowly within a disciplinary area of study. But, such specialization comes at a well-known cost: an intellectual narrowing that, in the limit, results in knowing everything about nothing and nothing about everything. It is due to precisely this dynamic that the phrase “it’s academic” has sadly come to be synonymous with “it’s irrelevant.”

Yet, despite evident costs to society as a whole, such long-term trends cannot be easily shifted, much less reversed. The reality today remains much as Jones found it to be a decade ago: without increased specialization, scientific discovery slows or ceases; without teamwork and collaboration across disciplinary boundaries, technological innovation slows or ceases. If technological complexity increases more rapidly than the average human life span, these two observations combine to suggest a sort of fundamental limit on the human potential to generate technological advance.

Will it someday be impossible to live long enough to acquire the knowledge needed to make advances on prior knowledge? Will new learning come to an end?

No. An end to technological evolution is no more likely than an end to biological evolution. The underlying reason is the same in both cases: the nearly unbounded power of combinatorial possibilities—the topic that was the focus of chapter 7.

If the current generations of techno-pessimists fail to see the creation of new combinations at work today, it’s simply because they either can’t glimpse them from where they sit, or they’re just not looking hard enough. Granted, the technologies that drove past prosperity in the United States—electric lights, the telephone, automobiles and airplanes, flush toilets—are today improving only incrementally in comparison with the past. But those very same technologies are only now reaching the majority of the world’s population. The resultant productivity gains are massive and reverberating in an epic fashion on a global scale. That process is just beginning.

What’s more, the infrastructure technologies that will define the nature of both business and government in the coming century are just now coming into use. Where twentieth-century technologies reshaped the world around economies of scale, twenty-first century technologies will shape the world once again, this time around economies of collaboration. For a new generation of innovators, overcoming complexity is the paramount challenge. As Martin Weitzman has astutely observed, “The ultimate limits to growth may lie not as much in our ability to generate new ideas, so much as in our ability to process an abundance of potentially new seed ideas into usable forms.” Contemporary tools are, unsurprisingly, particularly well suited to contemporary challenges: assessing the effectiveness of new combinations, rather than generating new building blocks.

As to whether that process—sorting the good ideas from the bad in a complex world—will itself ultimately get so difficult that human progress will terminate altogether in the twenty-third or twenty-fourth centuries, well, from a present-day standpoint, it’s academic.